Data input and parsing

# options(width=100)
options(width=90)
library(plyr)
library(dplyr)
library(ggplot2)
library(lme4)
library(reshape2)
computer = 'acer'  # 'shocky', 'station3', 'acer' are all possible options
if(computer == 'shocky' || computer == 'toshi'){ dropbox_dir='/Users/Egor/Dropbox/' }
if(computer == 'acer'){ dropbox_dir='/Users/egora/Dropbox/' }
source(paste(dropbox_dir, 'Projects/eb/eb/an/funs_an/BF_t.R', sep='/'))
source(paste(dropbox_dir, 'Projects/eb/eb/an/funs_an/BF_U.R', sep='/'))
library(R.utils)
sourceDirectory(paste(dropbox_dir, 'Projects/eb/eb/an/funs_an', sep='/'))
ds = read.csv(paste(dropbox_dir, 'Projects/eb/eb/an/consolidated/ds2.csv', sep='/'))
dsa = read.csv(paste(dropbox_dir, 'Projects/eb/eb/an/consolidated/dsa2.csv', sep='/'))
# Reordering levels of Condition variable, such that No Blink condition is the reference:
ds$Cond <- factor(ds$Cond, c('NoBlink','Artificial','Prompted')) # this works for lm

Continuous CTOA

# cur_subj = 8 #TEMP
for(cur_subj in unique(ds$subj)){
  p = ggplot(data=ds[ds$subj==cur_subj,], aes(x=ctoa, y=RT, color=CueValid)) + 
      geom_smooth(method='loess', alpha=0.15, aes(fill=CueValid), span=0.15) +
      geom_point(alpha=0.5) +
      xlab('Cue-to-Target Asynchrony (ms)') + ylab('RT (ms)') + facet_grid(Cond~.) +
      ggtitle(paste('Participant', as.character(cur_subj), 'RT')) + guides(alpha=F) +
      theme(panel.grid.minor=element_blank(), plot.title = element_text(hjust = 0.5))
  p = plot_themefy(p)
  plot(p)
}

# pdf('eb2_indiv.pdf', width=8.5, height=5.5)
# plot(p)
# dev.off()

Discontinuous CTOA

# sumss_valid = ddply(ds[ds$CueValid=='Valid',], .(subj, ctoa_lowbound, Cond), summarise, 
#                     RT_valid=median(RT), N_valid=length(RT))
# sumss_invalid = ddply(ds[ds$CueValid=='Invalid',], .(subj, ctoa_lowbound, Cond), summarise, 
#                       RT_invalid=median(RT), N_invalid=length(RT))
# sumss_adv = merge(sumss_valid, sumss_invalid, by=c('subj', 'ctoa_lowbound', 'Cond'))
# sumss_adv$rt_adv = sumss_adv$RT_invalid - sumss_adv$RT_valid
# for(cur_subj in unique(ds$subj)){
#   adv_subj = sumss_adv[sumss_adv$subj==cur_subj,]
#   p = ggplot(data=adv_subj, aes(x=ctoa_lowbound, y=rt_adv, color=Cond, alpha=0.5)) + 
#       geom_line() + xlab('Cue-to-Target Asynchrony (ms)') + 
#       ylab('RT Invalid - Valid (ms)') + 
#       theme(panel.grid.minor=element_blank(), plot.title = element_text(hjust = 0.5)) + 
#       ggtitle(paste('Participant', as.character(cur_subj))) + guides(alpha=F)
#   p = plot_themefy(p)
#   plot(p)
#   all_furs = data.frame()
#   for(cur_cond in unique(sumss_adv$Cond[sumss_adv$subj==cur_subj])){
#     this_fur = fur(adv_subj, cur_cond)
#     this_fur$Cond = cur_cond
#     all_furs = rbind(this_fur, all_furs)
#   }
#   p = ggplot(all_furs, aes(x=freq,y=A, color=Cond)) + geom_line() + xlim(.75,5.25) +
#     xlab('Frequency') + ylab('Amplitude') + guides(color=guide_legend(title='Blink Condition')) +
#     ggtitle(paste('Participant', as.character(cur_subj)))
#   p = plot_themefy(p)
#   suppressWarnings(plot(p))
#   # Printing number of trials in each condition:
#   print(dcast(melt(adv_subj[,c('ctoa_lowbound', 'Cond', 'N_valid', 'N_invalid')], 
#                    id.vars=c('ctoa_lowbound', 'Cond')), Cond + variable ~ ctoa_lowbound))
# }